Diabetologia (2012) 55:2142–2147 DOI 10.1007/s00125-012-2571-8
SHORT COMMUNICATION
Trends in childhood type 1 diabetes incidence in Europe during 1989–2008: evidence of non-uniformity over time in rates of increase C. C. Patterson & E. Gyürüs & J. Rosenbauer & O. Cinek & A. Neu & E. Schober & R. C. Parslow & G. Joner & J. Svensson & C. Castell & P. J. Bingley & E. Schoenle & P. Jarosz-Chobot & B. Urbonaité & U. Rothe & C. Krzisnik & C. Ionescu-Tirgoviste & I. Weets & M. Kocova & G. Stipancic & M. Samardzic & C. E. de Beaufort & A Green & G. G. Dahlquist & G. Soltész
Received: 30 December 2011 / Accepted: 2 April 2012 / Published online: 26 May 2012 # Springer-Verlag 2012
Abstract Aims/hypothesis The aim of the study was to describe 20year incidence trends for childhood type 1 diabetes in 23 EURODIAB centres and compare rates of increase in the first (1989–1998) and second (1999–2008) halves of the period. Methods All registers operate in geographically defined regions and are based on a clinical diagnosis. Completeness of registration is assessed by capture–recapture methodology.
Twenty-three centres in 19 countries registered 49,969 new cases of type 1 diabetes in individuals diagnosed before their 15th birthday during the period studied. Results Ascertainment exceeded 90% in most registers. During the 20-year period, all but one register showed statistically significant changes in incidence, with rates universally increasing. When estimated separately for the first and second halves of the period, the median rates of increase
Electronic supplementary material The online version of this article (doi:10.1007/s00125-012-2571-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users. C. C. Patterson (*) Centre for Public Health, Queen’s University Belfast, Institute of Clinical Science Block B, Grosvenor Road, Belfast BT12 6BJ, UK e-mail:
[email protected] E. Gyürüs : G. Soltész Department of Paediatrics, Pécs University, Pécs, Hungary J. Rosenbauer Institute of Biometrics and Epidemiology, German Diabetes Centre, Leibniz Institute for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany O. Cinek Department of Pediatrics, Second Faculty of Medicine, Charles University in Prague and University Hospital Motol, Prague, Czech Republic A. Neu University Children’s Hospital, Tübingen, Germany
E. Schober Department of Pediatric and Adolescent Medicine, Medical University of Vienna, Vienna, Austria R. C. Parslow Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, Leeds, UK G. Joner Department of Pediatrics, Ullevål University Hospital, Oslo, Norway J. Svensson Department of Paediatrics, University of Copenhagen, Herlev, Denmark C. Castell Department of Health, Government of Catalonia, Barcelona, Spain P. J. Bingley School of Clinical Sciences, University of Bristol, Bristol, UK
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were similar: 3.4% per annum and 3.3% per annum, respectively. However, rates of increase differed significantly between the first half and the second half for nine of the 21 registers with adequate coverage of both periods; five registers showed significantly higher rates of increase in the first half, and four significantly higher rates in the second half. Conclusions/interpretation The incidence rate of childhood type 1 diabetes continues to rise across Europe by an average of approximately 3–4% per annum, but the increase is not necessarily uniform, showing periods of less rapid and more rapid increase in incidence in some registers. This pattern of change suggests that important risk exposures differ over time in different European countries. Further time trend analysis and comparison of the patterns in defined regions is warranted. Keywords Epidemiology . Incidence . Temporal change . Trends . Type 1 diabetes
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in the 1990s, whereas in Europe there was clear evidence that relative increases were highest in central and eastern European countries and in the under-5-year age group during the period 1989–2003. More recent analyses from Norway [3] and Finland [4] suggest that rates of increase were lower in the 1980s, with a subsequent acceleration in the 1990s. The same pattern is evident in data from Sweden [5], and that analysis additionally raises the possibility that the rapid increase in the 1990s may soon be reversed, a reduction in rates having been observed beginning with the 2000 birth cohort. The EURODIAB group has maintained registers of childhood diabetes in a range of European countries since 1989 using standardised methodology and with validation of completeness of ascertainment, and these observations from Scandinavia led us to compare incidence rates in the first half of the 20-year registration period (1989–1998) with those in the second half (1999–2008).
Introduction Methods Recent incidence rate trends in childhood type 1 diabetes have been well characterised in publications by the EURODIAB registries in Europe [1] and by the DIAMOND (Diabetes Mondiale) Project Group worldwide [2]. The DIAMOND report described increasing trends in nearly every continent
Case inclusion criteria were as previously described for the EURODIAB registers [6]: new diagnoses of type 1 (insulindependent) diabetes mellitus among children aged under 15 years resident in the geographically defined region. The
E. Schoenle Department of Endocrinology and Diabetology, University Children’s Hospital, Zurich, Switzerland
M. Kocova Department of Endocrinology and Genetics, University Children’s Hospital, Skopje, Macedonia
P. Jarosz-Chobot Department of Pediatrics, Endocrinology and Diabetes, Medical University of Silesia, Katowice, Poland B. Urbonaité Institute of Endocrinology, Lithuanian University of Health Science, Kaunus, Lithuania U. Rothe Department for Epidemiology and Health Care Research, Technical University of Dresden, Dresden, Germany C. Krzisnik Department of Pediatrics, University Children’s Hospital, Ljubljana, Slovenia C. Ionescu-Tirgoviste Nutrition and Metabolic Diseases Clinic, N. Paulescu Institute of Diabetes and Metabolic Diseases, Bucharest, Romania I. Weets Diabetes Research Center, Brussels Free University, Brussels, Belgium
G. Stipancic Department of Paediatrics, University Hospital Sestre Milosrdnice, Zagreb, Croatia M. Samardzic Department of Endocrinology and Diabetes, University Children’s Hospital, Podgorica, Montenegro C. E. de Beaufort Department of Paediatric Diabetes and Endocrinology, Paediatric Clinic, Luxembourg, Luxembourg A. Green Odense Patient data Exploratory Network, University of Southern Denmark, Odense, Denmark G. G. Dahlquist Department of Clinical Science, University of Umeå, Umeå, Sweden
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completeness of registration was estimated separately in each of the 10-year periods using capture–recapture methodology [7], which requires that independent primary and secondary sources of ascertainment are available. In most centres, the primary source of ascertainment was through hospital records or notifications by paediatricians and family doctors, whereas secondary sources varied depending on local circumstances and included social insurance schemes, diabetes associations and prescription data. Annual estimates of the population resident in each centre’s geographically defined area were used as denominators for the calculation of directly standardised incidence rates using a standard population consisting of equal numbers of children in each of six subgroups defined by age group (0–4, 5–9 and 10–14 years) and sex.
Poisson regression was used to estimate the trends in incidence rate within centres. For each centre, a model with terms for age group, sex and an age group×sex interaction was first fitted. Then either a categorical variable representing the 5-year subperiods or a linear term testing for trend across individual years was added to the model to provide comparisons of incidence rates over time that took account of changes in the age structure of the population. For three centres whose registers changed coverage during the period, separate estimates of trend were fitted for each 10-year subperiod, and the two estimates were compared by likelihood ratio test. For the remaining centres, a similar model was fitted but with the added constraint that the fitted lines should meet between 1998 and 1999. Models were fitted using Stata Release 11 (Stata, College Station, TX, USA).
Table 1 Age and sex standardised rates of type 1 diabetes diagnosed before 15 years of age in four five year periods for 23 EURODIAB centres from 19 countries in Europe Centre
Austria Belgium Croatia Czech Republic Denmarkc
Region
Period
Number of cases
Standardised incidence rate per 100,000a P1
P2
P3
P4b
Whole nation Antwerp Zagreb Whole nation 1) Four counties 2) Whole nation Baden Württemberg
1989–2008 1989–2008 1989–2008 1989–2008 1989–1998 1999–2008 1989–2007
3372 448 339 4883 385 2402 4804
9.0 10.9 6.7 8.5 17.0 – 11.0
9.9 12.9 6.4 11.5 16.3 – 13.0
13.3 15.5 8.2 17.0 – 22.6 15.4
17.5 15.9 10.4 19.3 – 25.1 21.8d
Poland Romania Slovenia Spain Sweden Switzerland United Kingdom United Kingdom
1) Düsseldorf (seven districts) 2) North Rhine-Westphalia Saxony 18 counties Whole nation Whole nation Whole nation Whole nation 1) Eight counties 2) Whole nation Katowice Bucharest Whole nation Catalonia Stockholm county Whole nation Northern Ireland Oxford
1989–1998 1999–2008 1998–2008 1989–2008 1989–2008 1989–2008 1989–2008 1996–2008 1989–2003 2004–2008 1989–2008 1989–2008 1989–2008 1989–2008 1989–2008 1991–2008 1989–2008 1989–2008
595 6331 921 3239 1396 229 447 252 1380 1504 1719 534 715 2527 1978 2220 2043 2288
13.3 – – 9.0 7.3 11.4 3.2 – 21.1 – 5.2 4.7 7.9 12.4 25.8 8.0d 20.0 17.2
16.8 – 11.6d 10.7 8.2 12.3 3.9 10.1d 20.5 – 7.9 6.1 9.2 13.6 25.6 8.3 24.7 21.7
– 21.3 15.6 12.4 10.3 15.5 5.6 14.0 24.6 – 12.9 11.3 11.1 12.9 34.5 11.0 29.8 24.0
– 23.7 20.1 18.3 14.2 19.0 5.8 17.5 – 32.8 16.5 14.5 14.6 12.1 36.6 13.1 33.9 25.1
United Kingdom
Yorkshire
1989–2008
3018
16.1
19.7
23.5
25.5
Germany Germanyc Germany Hungary Lithuania Luxembourg Macedonia Montenegro Norwayc
a
Standard population with six age-sex subgroups of equal size
b
Periods denoted P1: 1989–1993, P2: 1994–1998, P3: 1999–2003, P4: 2004–2008
c
In three registries, period 2) has extended geographic coverage compared with period 1)
d
Rate based on registration data for only part of the period
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The Joinpoint regression program (Version 3.5 – April 2011; Statistical Methodology and Applications Branch and Data Modeling Branch, Surveillance Research Program National Cancer Institute, Bethesda, MD, USA) specifically designed for surveillance of trends in cancer incidence, was also used to see how sensitive conclusions were to the arbitrary division of the period into two 10-year subperiods. Joinpoint provides greater flexibility by accommodating the fitting of two or more linear segments that join at time points that are estimated from the data. The program provides a permutation
test to assess the number of linear segments and the times at which they join, while taking into account the multiple testing issues inherent in the approach. A less conservative Bayesian information criterion for model selection was also employed. In order that Joinpoint should mimic as closely as possible the Poisson regression approach, the log-linear model option was chosen, and heteroscedasticity was taken into account by using the standard error of the annual standardised rates. Further details are provided in the electronic supplementary material [ESM] Statistical methods.
Table 2 Completeness of ascertainment and estimated annual rates of increase compared in the two 10-year periods 1989–1998 and 1999–2008 for 23 EURODIAB centres Centre
Region
Completeness of ascertainment, % 1989–1998:1999–2008
Austria Belgium Croatia Czech Republic Denmarkb Germany Germanyb Germany Hungary Lithuania Luxembourg Macedonia Montenegro Norwayb Poland Romania Slovenia Spain Sweden Switzerland UK UK UK
Rates of increase per annum, %a (95 % CI) 1989–1998 : 1999–2008
p value
Whole nation Antwerp Zagreb Whole nation 1) Four counties 2) Whole nation Baden Württemberg 1) Düsseldorf (seven districts) 2) North Rhine–Westphalia Saxony
99.8 : 97.2 98.·6 : 94.·9 99.7 : 100.0 99.9 : 97.4 99.1 : ― ― : 99.2d 97.2 : 100.0 94.0 : ― ― : 98.6 ― : 93.6d
3.3 (1.8,4.8) : 3.3 (–0.6,7.4) : 0.1 (–4.3,4.7) : 7.6 (6.3,8.8) : 0.5 (–2.9,4.1)c : ―: 2.9 (1.7,4.2) : 6.1 (3.2,9.2)c : ―: ―:
6.1 (4.8,7.4) 1.9 (–1.6,5.5) 6.8 (2.7,11.0) 3.9 (2.9,5.0) ― 1.7 (0.2,3.1)c 6.5 (5.3,7.7)e ― 2.1 (1.3,3.0)c 4.6 (2.2,7.1)
0.03* 0.68 0.09 0.001* 0.56c
18 counties Whole nation Whole nation Whole nation Whole nation 1) Eight counties 2) Whole nation Katowice Bucharest Whole nation Catalonia Stockholm county Whole nation Northern Ireland Oxford Yorkshire
97.1 : 98.7 100.0 : n/a 100.0 : 100.0 94.9 : 100.0 100.0 : 100.0 100.0 : ― ― : 92.0d 99.9 : n/a 100.0 : 100.0 100.0 : 100.0 89.4 : 97.6 100.0 : n/a 91.7d: 91.3d 99.5 : 99.5 n/a : n/a 99.0 : 99.6
3.2 (1.8,4.7) : 2.1 (–0.1,4.3) : 0.9 (–4.7,6.8) : 6.4 (2.2,10.7) : ―: –1.2(–3.5,1.1)c : ―: 10.7 (8.3,13.1) : 8.0 (4.3,12.0) : 4.1 (1.0,7.2) : 0.9 (–0.5,2.4) : 2.5 (0.6,4.5) : 2.1 (–0.3,4.5)e : 4.6 (2.7,6.5) : 4.0 (2.3,5.8) : 4.7 (3.1,6.3) :
5.8 (4.5,7.2) 7.2 (5.1,9.3) 5.8 (0.9,10.8) 2.9 (–0.5,6.5) 6.5 (1.6,11.7) ― 0.5 (–3.0,4.2)c,e 5.5 (3.7,7.3) 7.8 (4.4,11.2) 3.9 (1.1,6.8) –1.4 (–2.9,0.1) 2.5 (0.9,4.2) 5.4 (3.8,7.0) 2.8 (1.2,4.5) 0.4 (–1.1,2.0) 1.6 (0.3,2.9)
0.04* 0.009* 0.32 0.33 ― 0.42c
0.002* 0.01*c ―
0.006* 0.93 0.96 0.09 0.66 0.07 0.27 0.02* 0.02*
a
Derived from Poisson regression model estimates of log-linear trends constraining lines to meet between 1998 and 1999 (see ESM Statistical methods)
b
In three registries, period 2) has extended geographic coverage compared with period 1)
c
Rates of increase in periods 1) and 2) were estimated and compared without constraining the fitted log-linear trends to meet between 1998 and 1999
d
Estimate was obtained independently of the EURODIAB study
e
Rate of increase was based on registration data for only part of the period
*p
